{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Copyright 2016-present, Facebook, Inc.\n",
    "# All rights reserved.\n",
    "\n",
    "# This source code is licensed under the license found in the\n",
    "# LICENSE-examples file in the root directory of this source tree."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Compare various biased sampling schemes\n",
    "There are a number of different ways that we can bias our sample. Each has its own advantages and disadvantages. We demonstrate the various advantages in terms of sample error and lift in positive examples examined. We all so demonstrate how base classifier performance can impact these values.\n",
    "\n",
    "Finally, we will demonstrate how one can use a two step sampling process to further reduce sampling error."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "from sklearn import linear_model\n",
    "\n",
    "import ml_sampler\n",
    "import tutorial_helpers"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Generate data\n",
    "As in the intro, we select the Covtype data to serve as the data we would like to sample. \n",
    "\n",
    "In practice, we wont know the 'truth' values of the dataset. We will have to sample and evaluate each record to determine if it is a positive example. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# https://archive.ics.uci.edu/ml/datasets/Covertype\n",
    "covtype_data = pd.read_csv('covtype.data', names=range(54)+['class'])\n",
    "\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "# lets use class == 5 as the 'spam' - totally made up but serves as a decent example\n",
    "X, y = covtype_data[covtype_data.columns - ['class']], covtype_data['class'] == 5\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.80, random_state=42)\n",
    "\n",
    "\n",
    "# for training purposes we want 50% 'spam' and 50% 'ham'\n",
    "# interesting to note that the classifier scores are not probabilities for the overall\n",
    "# dataset since we downsample negative examples\n",
    "num_train = len(y_train)\n",
    "num_pos = y_train.sum()\n",
    "samp_prob = num_pos * 1.0 / num_train\n",
    "\n",
    "train_sel = [True if y else np.random.rand() < samp_prob for y in y_train]\n",
    "\n",
    "\n",
    "\n",
    "def produce_data(pcnt_random=0.0):\n",
    "    \"\"\"Generate datasets based on the Covtype dataset. Train a simple logistic \n",
    "    regression to score each example in the held out data.\n",
    "    Args:\n",
    "        pcnt_random: Assign random values to this fraction of the dataset. This \n",
    "            effectively takes a good classifier and degrades the performance to\n",
    "            random chance.\n",
    "    \n",
    "    Returns:\n",
    "        is_positive: numpy.array of values indicating if the record is a\n",
    "            positive class.\n",
    "        scores: numpy.array of values indicating the model score.\n",
    "        num_samples: Number of samples to take.\n",
    "        bias_func: Function to apply to @scores. Serves to bias the sampling\n",
    "            procedure.\n",
    "    \"\"\"\n",
    "    # ROC AUC of this classifier is about 0.95\n",
    "    clf = linear_model.LogisticRegression(C=1.0, penalty='l1')\n",
    "    clf.fit(X_train[train_sel], y_train[train_sel])\n",
    "\n",
    "    # number of times the content was viewed \n",
    "    views = np.random.exponential(scale=5, size=len(y_test))\n",
    "\n",
    "    # is spam?\n",
    "    is_spam = y_test.values \n",
    "\n",
    "    # spam classifier scores\n",
    "    scores = clf.predict_proba(X_test)[:,1]\n",
    "    \n",
    "    num_random = len(scores)*pcnt_random\n",
    "\n",
    "    rand_index = np.random.choice(len(scores), num_random, replace=False)\n",
    "    \n",
    "    scores[rand_index] = np.random.random(size=num_random)\n",
    "\n",
    "    return views, is_spam, scores\n",
    "\n",
    "\n",
    "views, is_spam, scores = produce_data()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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Hn4F3cd31X9DSk3mm41ytAFbhrsdbRKSzl149ETkXVwwfbiy+QVXLarwfztO+XklOvOK5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\nRq3y+bTYAzWec9QePubEGGM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reZbhSqzaJZnGmUB3YHTJgKgm25RfyOKVm0ot33OXJmTY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\nrkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5ecc04e190>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# the classifier we trained in produce_data is actually pretty good\n",
    "tutorial_helpers.plot_roc(y_test, scores)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.6483618712920829"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# true prevalence of positive examples in the dataset (weighted by importance) \n",
    "views[is_spam].sum() / views.sum() * 100.0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Demonstrate helper functions "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Take a normal random sample that introduces no bias from the scores parameter we see that estimated prevalence roughly matches the true prevalence.\n",
    "\n",
    "Also note that the percent of positive records sampled (sampled_positive_percent) matches overall prevalence. This shows that we haven't biased our sample towards taking more positive examples."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{u'bound_width': 0.86050843646031128,\n",
       " u'coverage': True,\n",
       " u'est_prevalence': 1.4666666666666668,\n",
       " u'lower_bound': 1.0364124484365114,\n",
       " u'sampled_positive_percent': 1.4666666666666666,\n",
       " u'true_prevalence': 1.6483618712920829,\n",
       " u'upper_bound': 1.8969208848968226}"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# This function is very simple, it takes a sample given the parameters specified\n",
    "# then it computes prevalence and sampled_positive_percent.\n",
    "tutorial_helpers.sample_stats(\n",
    "    views, \n",
    "    is_spam, \n",
    "    np.ones(len(views)), \n",
    "    num_samples=3000,  \n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# do the above but many times (4k). \n",
    "# This gives us 95% confidence intervals for prevalence of 'is positive' in the population\n",
    "\n",
    "results = tutorial_helpers.simulated_sample_stats(\n",
    "    views, \n",
    "    is_spam, \n",
    "    np.ones(len(views)), \n",
    "    num_samples=3000, \n",
    "    num_iterations=400\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>bound_width</th>\n",
       "      <th>coverage</th>\n",
       "      <th>est_prevalence</th>\n",
       "      <th>lower_bound</th>\n",
       "      <th>sampled_positive_percent</th>\n",
       "      <th>true_prevalence</th>\n",
       "      <th>upper_bound</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.977</td>\n",
       "      <td>True</td>\n",
       "      <td>1.900</td>\n",
       "      <td>1.411</td>\n",
       "      <td>1.900</td>\n",
       "      <td>1.648</td>\n",
       "      <td>2.389</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.943</td>\n",
       "      <td>True</td>\n",
       "      <td>1.767</td>\n",
       "      <td>1.295</td>\n",
       "      <td>1.767</td>\n",
       "      <td>1.648</td>\n",
       "      <td>2.238</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.800</td>\n",
       "      <td>True</td>\n",
       "      <td>1.267</td>\n",
       "      <td>0.866</td>\n",
       "      <td>1.267</td>\n",
       "      <td>1.648</td>\n",
       "      <td>1.667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.907</td>\n",
       "      <td>True</td>\n",
       "      <td>1.633</td>\n",
       "      <td>1.180</td>\n",
       "      <td>1.633</td>\n",
       "      <td>1.648</td>\n",
       "      <td>2.087</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.010</td>\n",
       "      <td>True</td>\n",
       "      <td>2.033</td>\n",
       "      <td>1.528</td>\n",
       "      <td>2.033</td>\n",
       "      <td>1.648</td>\n",
       "      <td>2.538</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   bound_width coverage  est_prevalence  lower_bound  \\\n",
       "0        0.977     True           1.900        1.411   \n",
       "1        0.943     True           1.767        1.295   \n",
       "2        0.800     True           1.267        0.866   \n",
       "3        0.907     True           1.633        1.180   \n",
       "4        1.010     True           2.033        1.528   \n",
       "\n",
       "   sampled_positive_percent  true_prevalence  upper_bound  \n",
       "0                     1.900            1.648        2.389  \n",
       "1                     1.767            1.648        2.238  \n",
       "2                     1.267            1.648        1.667  \n",
       "3                     1.633            1.648        2.087  \n",
       "4                     2.033            1.648        2.538  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "est_prevalence:\n",
      "\tValue: 1.6333\n",
      "\t95% Confidence Interval: (1.2325, 2.1333)\n",
      "\t\tCI Width: 0.90083\n",
      "\n",
      "sampled_positive_percent:\n",
      "\tValue: 1.6333\n",
      "\t95% Confidence Interval: (1.2325, 2.1333)\n",
      "\t\tCI Width: 0.90083\n",
      "\n",
      "Avg. Coverage: 0.945\n",
      "Avg. Confidence Interval Width: 0.908405265306\n"
     ]
    }
   ],
   "source": [
    "for c in ['est_prevalence', 'sampled_positive_percent']:\n",
    "    print '{}:'.format(c)\n",
    "    tutorial_helpers.print_confidence_interval(results[c].quantile([0.025, 0.5,  0.975]), '\\t')\n",
    "    print\n",
    "    \n",
    "print 'Avg. Coverage: {}'.format(results.coverage.mean())\n",
    "print 'Avg. Confidence Interval Width: {}'.format(results.bound_width.mean())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Create bias functions \n",
    "(To be evaluated below)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# these bins are used for the various bias functions and for plotting\n",
    "bins = np.linspace(0, 1, 10)\n",
    "\n",
    "# make some convenience functions for use below\n",
    "# see bias_functions for information on each method\n",
    "\n",
    "def pdf_func(scores):\n",
    "    return ml_sampler.interpolated_pdf_reciprocal(\n",
    "        scores, \n",
    "        bins=bins\n",
    "    )\n",
    "\n",
    "def bin_weights_func(scores):\n",
    "    return ml_sampler.bin_weights_raw(\n",
    "        scores, \n",
    "        bins=bins, \n",
    "        # note: we pick extreme weights in order to draw some distinctions below\n",
    "        #   this weight selection heavily favors higher score bins\n",
    "        bin_weights=np.logspace(1, 5.0, 10)\n",
    "    )\n",
    "\n",
    "# Methods are visualized below\n",
    "methods = [\n",
    "    # Normal probability proportionate to size sampling\n",
    "    ('PPS Sample', lambda score: np.ones(len(score))),    \n",
    "    \n",
    "    # Bias the sample to take equal samples from each score bin\n",
    "    ('Score Frequency', pdf_func), \n",
    "\n",
    "    # Use the raw model scores to bias the sample.\n",
    "    # Things that hive higher scores are proportionately higher to be \n",
    "    # samples.\n",
    "    ('Score Values', lambda score: score),\n",
    "    \n",
    "    # Use the raw model scores to bias the sample.\n",
    "    # Things that hive higher scores are proportionately higher to be \n",
    "    # samples.\n",
    "    ('sqrt(Score Values)', lambda score: np.sqrt(score)),\n",
    "]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot ROC-AUC and the distribution of scores sampled\n",
    "Each method produces an unbiased estimate of prevalence even as the model's performance improves. Statements below based on visual inspection of this limited sample. More principled plots found just below this section.\n",
    "\n",
    "**PPS Sample** - Has the same distribution of scores as in the broader sample.\n",
    "\n",
    "**Uniform Scores** - Has a flat distribution of scores. A safe default.\n",
    "\n",
    "**Scores** - Should be biased towards higher score bins but can be influenced by the overall population's distribution."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x7f5ec66df750>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Bfpbu/iqbsyctQ7N+2n8aMfP0CUT/shlppun8edYh+r7NA/5oZvua2R1mdnA6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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5ecc0a8d50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = plt.hist(scores, bins=bins)\n",
    "plt.title('Histogram of scores\\nin the full population')\n",
    "plt.xlabel('Score')\n",
    "plt.ylabel('Frequency')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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cF1O6i4AjGlz3oGw39Yg6k7j3bA48aWavEj2cLk3ry35gVVfnFAUvWYPgfNqt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\nrkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5ec66dfbd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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FaTYlBmGDiuPY5Oc5LwvUziNKkOYTQYrIatWSNifpl9QfiVEWVxn2Oa0zHjiL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\nKk5ERESkUlSciIiISKWoOBEREZFK+S+xTH2v0G+KwQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5eb71e9a10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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X6v7K2Yzelq6F/dY0JsKrdtzt6E3i9TQ0OK/h85xagvqSdSX9jRhqLjKgNJRz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\n9nKvO/0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5ec666fa90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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2czO/32qyRtMPN5BGhjgFJ9IRqd7+kDRK6tHExXYSqatp6tnwlbJku6XpAzXu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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5ec67c2d10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for name, func in methods:\n",
    "    \n",
    "    index, weights = ml_sampler.biased_sample(\n",
    "        biases=func(scores), \n",
    "        weights=views, \n",
    "        num_samples=3000,\n",
    "    )\n",
    "    \n",
    "    plt.show()\n",
    "    pd.Series(scores[index]).hist(bins=bins)\n",
    "    plt.title('Sampled score distribution for:\\n'+name)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Evaluate the various biases in terms of ROC AUC\n",
    "Investigate how model performance influences the various bias functions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "results = []\n",
    "\n",
    "for rnd in [0.0, 0.2, 0.4, 0.6, 0.8, 1.0]:\n",
    "    \n",
    "    # as rnd increases the model performance gets worse\n",
    "    views, is_spam, scores = produce_data(pcnt_random=rnd)  \n",
    "    \n",
    "    auc = tutorial_helpers.get_auc(is_spam, scores) \n",
    "    \n",
    "    for method, func in methods:\n",
    "        for i in range(7):\n",
    "            r = tutorial_helpers.sample_stats(views, is_spam, func(scores), num_samples=1000)\n",
    "            \n",
    "            r['ROC AUC'] = auc\n",
    "            # introduce a little jitter to make the plots easier to view\n",
    "            r['ROC AUC'] += np.random.rand() / 30.\n",
    "            \n",
    "            r['method'] = method\n",
    "            results.append(r)\n",
    "            \n",
    "results = pd.DataFrame(results)        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ROC AUC</th>\n",
       "      <th>bound_width</th>\n",
       "      <th>coverage</th>\n",
       "      <th>est_prevalence</th>\n",
       "      <th>lower_bound</th>\n",
       "      <th>method</th>\n",
       "      <th>sampled_positive_percent</th>\n",
       "      <th>true_prevalence</th>\n",
       "      <th>upper_bound</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.924</td>\n",
       "      <td>1.736</td>\n",
       "      <td>True</td>\n",
       "      <td>2.000</td>\n",
       "      <td>1.132</td>\n",
       "      <td>PPS Sample</td>\n",
       "      <td>2.000</td>\n",
       "      <td>1.649</td>\n",
       "      <td>2.868</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.917</td>\n",
       "      <td>1.778</td>\n",
       "      <td>True</td>\n",
       "      <td>2.100</td>\n",
       "      <td>1.211</td>\n",
       "      <td>PPS Sample</td>\n",
       "      <td>2.100</td>\n",
       "      <td>1.649</td>\n",
       "      <td>2.989</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.913</td>\n",
       "      <td>1.508</td>\n",
       "      <td>True</td>\n",
       "      <td>1.500</td>\n",
       "      <td>0.746</td>\n",
       "      <td>PPS Sample</td>\n",
       "      <td>1.500</td>\n",
       "      <td>1.649</td>\n",
       "      <td>2.254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.901</td>\n",
       "      <td>1.974</td>\n",
       "      <td>True</td>\n",
       "      <td>2.600</td>\n",
       "      <td>1.613</td>\n",
       "      <td>PPS Sample</td>\n",
       "      <td>2.600</td>\n",
       "      <td>1.649</td>\n",
       "      <td>3.587</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.906</td>\n",
       "      <td>1.693</td>\n",
       "      <td>True</td>\n",
       "      <td>1.900</td>\n",
       "      <td>1.053</td>\n",
       "      <td>PPS Sample</td>\n",
       "      <td>1.900</td>\n",
       "      <td>1.649</td>\n",
       "      <td>2.747</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ROC AUC  bound_width coverage  est_prevalence  lower_bound      method  \\\n",
       "0    0.924        1.736     True           2.000        1.132  PPS Sample   \n",
       "1    0.917        1.778     True           2.100        1.211  PPS Sample   \n",
       "2    0.913        1.508     True           1.500        0.746  PPS Sample   \n",
       "3    0.901        1.974     True           2.600        1.613  PPS Sample   \n",
       "4    0.906        1.693     True           1.900        1.053  PPS Sample   \n",
       "\n",
       "   sampled_positive_percent  true_prevalence  upper_bound  \n",
       "0                     2.000            1.649        2.868  \n",
       "1                     2.100            1.649        2.989  \n",
       "2                     1.500            1.649        2.254  \n",
       "3                     2.600            1.649        3.587  \n",
       "4                     1.900            1.649        2.747  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "colors = ['orange', 'royalblue', 'grey', 'lightblue', 'purple']\n",
    "\n",
    "def plot_vs_auc(results, col):\n",
    "    \"\"\"Plot various statistics as a function of ROC AUC\"\"\"\n",
    "    ax = None\n",
    "    i = 0\n",
    "    for method, func in methods:\n",
    "        df = results[results.method==method]\n",
    "\n",
    "        ax = df.plot(\n",
    "            x='ROC AUC', \n",
    "            y=col, \n",
    "            kind='scatter', \n",
    "            label=method, \n",
    "            ax=ax, \n",
    "            color=colors[i],\n",
    "            figsize=(10, 7),\n",
    "            s=40\n",
    "        )\n",
    "        plt.legend(loc='upper left')\n",
    "        i += 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Prevalence estimate vs ROC AUC\n",
    "Each method produces an unbiased estimate of prevalence even as the model's performance improves. Statements below based on visual inspection of this limited sample. More principled plots found just below this section.\n",
    "\n",
    "**PPS Sample** - Not impacted by model performance b/c bias is ignored. Tight grouping which suggests relatively low variance.\n",
    "\n",
    "**Uniform Scores** - Tight grouping which suggests relatively low variance. Variance reduces as model performance improves.\n",
    "\n",
    "**Scores** - Tight grouping which suggests relatively low variance. Variance reduces as model performance improves.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 3.5)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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PsUg3/kKfmZlpkWYcHerXb4BFsHerBQsWYGtry7BhI62me3h4kZycdNv23o4x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\ntw8CcynncFFErGz9APe1Pa69l28nVo3W6TRhy4bAbvXP9uGsT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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5ece6dff90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_vs_auc(results, 'est_prevalence')\n",
    "plt.ylim(0, 3.5)\n",
    "# note jitter was introduced to AUC to make the plots easier to read"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Percent sampled positive vs ROC AUC\n",
    "Each method produces an unbiased estimate of prevalence even as the model's performance improves. Statements below based on visual inspection of this limited sample. More principled plots found just below this section.\n",
    "\n",
    "**PPS Sample** - Not impacted by model performance b/c bias is ignored. No improvement in positive examples sampled as model performance improves.\n",
    "\n",
    "**Uniform Scores** - Moderate improvement in positive examples sampled as model performance improves.\n",
    "\n",
    "**Scores** - Moderate improvement in positive examples sampled as model performance improves."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 6.5)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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W65qK+/33jVy+fInHHhtgddt8Ly8vVFUlIyPDdGz9+jUoikK/fv0t6ru7u1ud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\nV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uTXtuNX5lIjDGsu1VVJDdQy+6vQ/knD2lemkXPG9gf+DGSmJGZPtJdUY4bX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\nSVID/wGeVk7C/Na/OQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5eb70a8990>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# All methods show increasing number of positive examples sampled as ROC-AUC improves\n",
    "# for the classifier (except the no bias method)\n",
    "plot_vs_auc(results, 'sampled_positive_percent')\n",
    "plt.ylim(0, 6.5)\n",
    "# note jitter was introduced to AUC to make the plots easier to read"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Use simulations to understand the variance of each bias  function\n",
    "Looking at the above (small) samples can give intuition for what is going on. Below we do a more through analysis prevalence and sampled_positive_percent with error bars."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "simulated_auc_results = []\n",
    "\n",
    "# this takes a loooooong time\n",
    "pcnt_rand = [0.0, 0.2, 0.4, 0.6, 0.8, 1.0]\n",
    "for rnd in pcnt_rand:\n",
    "    \n",
    "    # As rnd increases the model performance gets worse\n",
    "    views, is_spam, scores = produce_data(pcnt_random=rnd)    \n",
    "    \n",
    "    auc = tutorial_helpers.get_auc(is_spam, scores)\n",
    "    \n",
    "    i = 1\n",
    "    for method, func in methods:\n",
    "        \n",
    "        simulated_results = tutorial_helpers.simulated_sample_stats(\n",
    "            views, is_spam, func(scores), num_samples=3000, num_iterations=4000)\n",
    "        \n",
    "        simulated_results['AUC'] = auc \n",
    "        simulated_results['method'] = method\n",
    "        \n",
    "        simulated_auc_results.append(simulated_results)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "auc_results = pd.concat(simulated_auc_results)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>bound_width</th>\n",
       "      <th>coverage</th>\n",
       "      <th>est_prevalence</th>\n",
       "      <th>lower_bound</th>\n",
       "      <th>sampled_positive_percent</th>\n",
       "      <th>true_prevalence</th>\n",
       "      <th>upper_bound</th>\n",
       "      <th>AUC</th>\n",
       "      <th>method</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.811</td>\n",
       "      <td>True</td>\n",
       "      <td>1.300</td>\n",
       "      <td>0.895</td>\n",
       "      <td>1.300</td>\n",
       "      <td>1.672</td>\n",
       "      <td>1.705</td>\n",
       "      <td>0.901</td>\n",
       "      <td>PPS Sample</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.831</td>\n",
       "      <td>True</td>\n",
       "      <td>1.367</td>\n",
       "      <td>0.951</td>\n",
       "      <td>1.367</td>\n",
       "      <td>1.672</td>\n",
       "      <td>1.782</td>\n",
       "      <td>0.901</td>\n",
       "      <td>PPS Sample</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.851</td>\n",
       "      <td>True</td>\n",
       "      <td>1.433</td>\n",
       "      <td>1.008</td>\n",
       "      <td>1.433</td>\n",
       "      <td>1.672</td>\n",
       "      <td>1.859</td>\n",
       "      <td>0.901</td>\n",
       "      <td>PPS Sample</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.969</td>\n",
       "      <td>True</td>\n",
       "      <td>1.867</td>\n",
       "      <td>1.382</td>\n",
       "      <td>1.867</td>\n",
       "      <td>1.672</td>\n",
       "      <td>2.351</td>\n",
       "      <td>0.901</td>\n",
       "      <td>PPS Sample</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.934</td>\n",
       "      <td>True</td>\n",
       "      <td>1.733</td>\n",
       "      <td>1.266</td>\n",
       "      <td>1.733</td>\n",
       "      <td>1.672</td>\n",
       "      <td>2.200</td>\n",
       "      <td>0.901</td>\n",
       "      <td>PPS Sample</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   bound_width coverage  est_prevalence  lower_bound  \\\n",
       "0        0.811     True           1.300        0.895   \n",
       "1        0.831     True           1.367        0.951   \n",
       "2        0.851     True           1.433        1.008   \n",
       "3        0.969     True           1.867        1.382   \n",
       "4        0.934     True           1.733        1.266   \n",
       "\n",
       "   sampled_positive_percent  true_prevalence  upper_bound   AUC      method  \n",
       "0                     1.300            1.672        1.705 0.901  PPS Sample  \n",
       "1                     1.367            1.672        1.782 0.901  PPS Sample  \n",
       "2                     1.433            1.672        1.859 0.901  PPS Sample  \n",
       "3                     1.867            1.672        2.351 0.901  PPS Sample  \n",
       "4                     1.733            1.672        2.200 0.901  PPS Sample  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "auc_results.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### ANALYSIS\n",
    "**PPS Sample** - Has consistent variance across model improvements.\n",
    "\n",
    "**Uniform Scores**- Variance reduces and sampled_positive_percent increases as the model improves.\n",
    "\n",
    "**Scores** - Variance reduces and sampled_positive_percent increases as the model improves."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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N10R3Pzm3zZjcW5tk69PP8u5+QZldZDddmwAGjHf3UcBCdI6JWo/OG+6WMLN9gUuIm6Uj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\nriaCuA2A7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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5ece6ff810>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "rand_offsets = [x / 200. for x in range(len(methods))]\n",
    "\n",
    "for i, c in enumerate([tup[0] for tup in methods]):\n",
    "    data = auc_results[auc_results.method==c].groupby('AUC')\n",
    "\n",
    "    prevalence = data.est_prevalence.mean().sort_index()    \n",
    "    low_err = data.est_prevalence.quantile(0.025).sort_index()\n",
    "    high_err = data.est_prevalence.quantile(0.975).sort_index()\n",
    "    \n",
    "    high_err = high_err - prevalence\n",
    "    low_err = prevalence - low_err\n",
    "\n",
    "\n",
    "    fig = plt.errorbar(\n",
    "        prevalence.index + rand_offsets[i], \n",
    "        prevalence, \n",
    "        yerr=(low_err, high_err), \n",
    "        color=colors[i], label=c\n",
    "    )\n",
    "    \n",
    "\n",
    "plt.legend(loc='center left', bbox_to_anchor=(1.0, 0.5))\n",
    "plt.title('Prevalence\\n(with emperical error bars)')\n",
    "plt.ylabel('Prevalence')\n",
    "plt.xlabel('Model ROC AUC')\n",
    "plt.show()    \n",
    "\n",
    "# note jitter was introduced to AUC to make the plots easier to read"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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S24wlNEODysezZ5xW6jOVl6Sc44uzrwGY2SeAAwk3g10y2RWppklSHrJck3Ufr3UdHLlY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\nEREREZES/H/J2Oftu5MATAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5e97bbb8d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "rand_offsets = [x / 200. for x in range(len(methods))]\n",
    "\n",
    "for i, c in enumerate([tup[0] for tup in methods]):\n",
    "\n",
    "    data = auc_results[auc_results.method==c].groupby('AUC')\n",
    "    \n",
    "    low_err = data.sampled_positive_percent.quantile(0.025).sort_index()\n",
    "    high_err = data.sampled_positive_percent.quantile(0.975).sort_index()\n",
    "    prevalence = data.sampled_positive_percent.mean().sort_index()\n",
    "    \n",
    "        \n",
    "    high_err = high_err - prevalence\n",
    "    low_err = prevalence - low_err\n",
    "    \n",
    "    fig = plt.errorbar(\n",
    "        prevalence.index + rand_offsets[i], \n",
    "        prevalence, \n",
    "        yerr=(low_err, high_err), \n",
    "        color=colors[i], label=c\n",
    "    )\n",
    "\n",
    "\n",
    "plt.legend(loc='center left', bbox_to_anchor=(1.0, 0.5))\n",
    "plt.title('Percent of Positive Samples\\n(with emperical error ears)')\n",
    "plt.ylabel('Percent of Positive')\n",
    "plt.xlabel('Model ROC AUC')\n",
    "plt.show()\n",
    "\n",
    "\n",
    "# note jitter was introduced to AUC to make the plots easier to read"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Itm4gMLaPxmc/RKj/sZzz1O79V8KdWxg8/nvEl5xb5AZUzlgyhQyP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HAAAg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\nP58QeP3O3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yXpZ4B/E3rIPlhAeRcTVkO/Mz3ogtY1xbYS5m+NIaxsnU1t3B4XGX2kfA4e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\nrkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5eb7002cd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for i, c in enumerate([tup[0] for tup in methods]):\n",
    "    df = auc_results[auc_results.method == c]\n",
    "    (df.groupby('AUC').coverage.mean() * 100).plot(label=c, color=colors[i])\n",
    "    \n",
    "plt.legend(loc='center left', bbox_to_anchor=(1.0, 0.5))\n",
    "plt.title('Percent of time estimated error bars\\ncover the true mean')\n",
    "plt.ylabel('Percent Coverage')\n",
    "plt.xlabel('Model ROC AUC')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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fxpXJcuBiXBm9CbgAOAD8Hvh3Vd1f4J5L6jeitIViEZGHgKuAW1X1yznCVABr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xbjZtjY+7vUbpsSa5cAh8JJXSxXAD0JZV+39LHbT6hqLhGdE1vmYTnwSRG5E5NM8BOAE2vnkXxu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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5eb7043390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for i, c in enumerate([tup[0] for tup in methods]):\n",
    "    df = auc_results[auc_results.method == c]\n",
    "    df.groupby('AUC').bound_width.mean().plot(label=c, color=colors[i])\n",
    "    \n",
    "plt.legend(loc='center left', bbox_to_anchor=(1.0, 0.5))\n",
    "plt.title('Estimated 95% Confidence Interval Width\\n(calculated from sample variance)')\n",
    "plt.ylabel('Percentage Width')\n",
    "plt.xlabel('Model ROC AUC')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Optimum bin allocation\n",
    "We can measure the variance in each bin to re-weight our sample to sample more from the bins that have the most variance. This serves to further reduce the variance associated with the sample.\n",
    "\n",
    "For more information see Optimum Allocation on the Wikipedia entry for Stratified Sampling - https://en.wikipedia.org/wiki/Stratified_sampling#Stratified_sampling_strategies"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Set bin weights to variance for each bin to reduce variance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "views, is_spam, scores = produce_data()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# take a sample to get a good number of samples per bin\n",
    "index, p_sample = ml_sampler.biased_sample(\n",
    "    \n",
    "    biases=ml_sampler.interpolated_pdf_reciprocal(scores, bins), \n",
    "    weights=views, \n",
    "    # take a lot of samples so that we have a good number per bin\n",
    "    #  the more samples we have per bin the more sure we can be in \n",
    "    #  the variance calculation for each bin\n",
    "    num_samples=20000,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# calculate the standard deviation per bin\n",
    "\n",
    "stdevs = []\n",
    "\n",
    "for l, h in [(bins[i-1], bins[i]) for i in range(1,len(bins))]:\n",
    "    sel = scores[index] >= l\n",
    "    sel &= scores[index] - 0.000001 < h\n",
    "    \n",
    "    est_var = ml_sampler.estimated_variance(views[index[sel]], p_sample[sel], is_spam[index[sel]]) \n",
    "    \n",
    "    stdevs.append(np.sqrt(est_var))\n",
    "    \n",
    "stdevs = np.array(stdevs)\n",
    "stdevs += stdevs.sum()/100."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# use the stdevs as bin weights, this means we sample more from bins with higher stdevs\n",
    "def variance_reducing_func(scores): \n",
    "    return ml_sampler.bin_weights_corrected(scores, bins, stdevs) \n",
    "\n",
    "opt_index, opt_weights = ml_sampler.biased_sample(\n",
    "    biases=variance_reducing_func(scores),\n",
    "    weights=views,     \n",
    "    num_samples=3000,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x7f5e94f970d0>"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Eve4Q82RjgcwpSaaFwZqvRnInWjlGrRjp45t99qZ/0dZxfPOyG/e8BpvvmjlGQ61nuM+b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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5e94fbe8d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pd.Series(scores[opt_index]).hist()\n",
    "plt.title('Sampled score distribution for:\\nVariance Reducing Weights')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Estimate the 95% confidence intervals for each method\n",
    "For comparison with the optimum bin allocation method below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "simulated_results = []\n",
    "\n",
    "# takes a bit\n",
    "for name, func in methods + [(\"'Optimum Allocation'\", variance_reducing_func)]:\n",
    "    # This function produces simulated confidence interval estimates for\n",
    "    #  the prevalence of positive examples in our population. This measures\n",
    "    #  the accuracy & precision of each method. Ideally we should have \n",
    "    #  values that match the overall population percentage \n",
    "    res = tutorial_helpers.simulated_sample_stats(views, is_spam, func(scores), 1000)\n",
    "    \n",
    "    simulated_results.append((name, res))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>bound_width</th>\n",
       "      <th>coverage</th>\n",
       "      <th>est_prevalence</th>\n",
       "      <th>lower_bound</th>\n",
       "      <th>sampled_positive_percent</th>\n",
       "      <th>true_prevalence</th>\n",
       "      <th>upper_bound</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.693</td>\n",
       "      <td>True</td>\n",
       "      <td>1.900</td>\n",
       "      <td>1.053</td>\n",
       "      <td>1.900</td>\n",
       "      <td>1.647</td>\n",
       "      <td>2.747</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.405</td>\n",
       "      <td>True</td>\n",
       "      <td>1.300</td>\n",
       "      <td>0.598</td>\n",
       "      <td>1.300</td>\n",
       "      <td>1.647</td>\n",
       "      <td>2.002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.508</td>\n",
       "      <td>True</td>\n",
       "      <td>1.500</td>\n",
       "      <td>0.746</td>\n",
       "      <td>1.500</td>\n",
       "      <td>1.647</td>\n",
       "      <td>2.254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.556</td>\n",
       "      <td>True</td>\n",
       "      <td>1.600</td>\n",
       "      <td>0.822</td>\n",
       "      <td>1.600</td>\n",
       "      <td>1.647</td>\n",
       "      <td>2.378</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.457</td>\n",
       "      <td>True</td>\n",
       "      <td>1.400</td>\n",
       "      <td>0.671</td>\n",
       "      <td>1.400</td>\n",
       "      <td>1.647</td>\n",
       "      <td>2.129</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   bound_width coverage  est_prevalence  lower_bound  \\\n",
       "0        1.693     True           1.900        1.053   \n",
       "1        1.405     True           1.300        0.598   \n",
       "2        1.508     True           1.500        0.746   \n",
       "3        1.556     True           1.600        0.822   \n",
       "4        1.457     True           1.400        0.671   \n",
       "\n",
       "   sampled_positive_percent  true_prevalence  upper_bound  \n",
       "0                     1.900            1.647        2.747  \n",
       "1                     1.300            1.647        2.002  \n",
       "2                     1.500            1.647        2.254  \n",
       "3                     1.600            1.647        2.378  \n",
       "4                     1.400            1.647        2.129  "
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "PPS Sample:\n",
      "\tprevalence:\n",
      "\t\tValue: 1.6000\n",
      "\t\t95% Confidence Interval: (0.9000, 2.5000)\n",
      "\t\t\tCI Width: 1.60000\n",
      "\n",
      "Score Frequency:\n",
      "\tprevalence:\n",
      "\t\tValue: 1.6379\n",
      "\t\t95% Confidence Interval: (1.1594, 2.2033)\n",
      "\t\t\tCI Width: 1.04388\n",
      "\n",
      "Score Values:\n",
      "\tprevalence:\n",
      "\t\tValue: 1.6402\n",
      "\t\t95% Confidence Interval: (1.2022, 2.1262)\n",
      "\t\t\tCI Width: 0.92395\n",
      "\n",
      "sqrt(Score Values):\n",
      "\tprevalence:\n",
      "\t\tValue: 1.6458\n",
      "\t\t95% Confidence Interval: (1.1315, 2.2020)\n",
      "\t\t\tCI Width: 1.07058\n",
      "\n",
      "'Optimum Allocation':\n",
      "\tprevalence:\n",
      "\t\tValue: 1.6360\n",
      "\t\t95% Confidence Interval: (1.2129, 2.1147)\n",
      "\t\t\tCI Width: 0.90179\n",
      "\n"
     ]
    }
   ],
   "source": [
    "for method, result in simulated_results:\n",
    "    print '{}:'.format(method)\n",
    "    print '\\tprevalence:'\n",
    "    tutorial_helpers.print_confidence_interval(result.est_prevalence.quantile([0.025, 0.5, 0.975]), '\\t\\t')\n",
    "    print \n",
    "        "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Analysis\n",
    "In this situation both Optimum Allocation and the Score methods give good results. Theoretically, Optimum Allocation produces the best results - it is highly dependent on the quality of the initial sample. A bad initial sample can produce results that are slightly worse than Score Adjusted but typically still better than the other methods. "
   ]
  }
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